MODELING OF CRISIS PHENOMENA IN REGIONAL STOCK MARKETS BY WAVELET-ENTROPY METHOD

Abstract

The article reflects the results of a study on modelling regional stock markets using wavelet entropy. Particular attention is paid to periods of crises as special states of markets. Countries with the developed economies were selected for the study, namely, the United States, United Kingdom, Germany, France, China, Japan and Hong Kong. The values of stock indices of regional stock markets were used as a statistical base. The research period is from 2015 to 2021. The aim of the article is to monitor the current state of markets and to demonstrate the possibilities of using the wavelet entropy index as a precursor of crisis phenomena.

The wavelet entropy method was used. All calculations were performed in the Matlab environment - a system for modeling nonlinear dynamical systems.

The results of the study demonstrate the absence of crisis phenomena in these markets as of April 2021. It is shown that the use of wavelet entropy as a precursor indicator is reasonable. In particular, the reaction of stock markets to such crisis situations as the COVID-19 pandemic as well as other socio-political events is shown.

Based on the results of calculations, conclusions are made about the current state of stock markets of the studied countries. All stock market participants, investors, and relevant ministries to develop effective strategies can use the results obtained, as well as the method in general.